CN115622888A - Cross-domain fusion constellation design method based on multidisciplinary cooperation reverse optimization - Google Patents
Cross-domain fusion constellation design method based on multidisciplinary cooperation reverse optimization Download PDFInfo
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Abstract
The invention discloses a cross-domain fusion constellation design method based on multidisciplinary collaborative reverse optimization, which comprises the steps of independently designing a constellation of each functional domain based on task requirements and basic parameter constraints of the constellation to obtain a basic constellation of each functional domain; synthesizing the basic constellation of each functional domain based on cooperative optimization to obtain an initial cross-domain fusion constellation, wherein the target of cooperative optimization can be set but is not limited to be the minimum system cost; and performing reverse optimization on the initial cross-domain fusion constellation, eliminating redundant satellites in the initial cross-domain fusion constellation and deploying optimized satellite loads to obtain the cross-domain fusion constellation. The invention is applied to the field of constellations, divides the constellation design into a comprehensive basic constellation design meeting the requirements and a cross-domain fusion reverse design optimization of the basic constellation, not only can meet the requirements of multi-domain fusion constellation design such as communication, navigation, remote sensing and the like, but also can optimize aiming at an optimization target, effectively improves the design efficiency of the basic constellation and meets the comprehensive requirements of various services.
Description
Technical Field
The invention relates to the technical field of constellation design, in particular to a communication, navigation and remote sensing integrated cross-domain fusion constellation design method based on multidisciplinary cooperation reverse optimization.
Background
The aerospace system is developed to the present, and the current typical aerospace system has functional systems such as satellite navigation, communication, remote sensing and the like. Such as GPS, starlink, skysat, etc. However, these constellations are all for a single function, and only a certain class of services can be provided. They are called domains, defined as a set of connected devices and user terminals with a specific functionality. With the development of software-defined satellites and intelligent satellite technologies, people begin to consider the interconnection, sharing and fusion construction of each constellation system. Network performance can be significantly enhanced if the resources of the various domains (e.g., communication domain and observation domain) can be coordinated. Therefore, in recent years, many satellite cross-domain related researches, such as cross-domain resource scheduling and resource virtualization for supporting cross-domain, have appeared. A communication fusion system and a communication remote sensing fusion system are provided. However, with the development of software-defined satellite technology, satellite edge computing technology and further enhancement of satellite processing capability, people further develop the satellite cross-domain, and progress towards integration and even intellectualization. The integrated and intelligent space-based system has the advantages of improving the utilization rate of satellite resources, shortening the task response time and improving the service quality. But with the problem that space-based systems require more complex designs, especially constellation design challenges that are among the most relevant to system performance.
Conventional constellation designs are directed to a single class of functions, i.e., a single domain. Due to the different needs, there are constellations of different functions, global or regional, and navigation, communication, remote sensing, radar, etc. Different constellation configurations, different designs and different design methods are adopted during design. However, such design methods cannot satisfy the constellation design of integrated cross-domain fusion. The main difficulty is that the integrated cross-domain fused constellation is equivalent to a constellation system with multiple fused requirements. When multiple services are fused together, the difficulty of modeling and solving of constellation design is further increased. Except for the calculation space explosion existing in the design of the field of the space-based system, the constellation function of cross-domain fusion can be reconstructed as required, so that the satellite function is uncertain, and the constellation design is extremely difficult.
In the existing research, a concept of a hybrid satellite constellation consisting of satellites with multiple functions is provided, the hybrid constellation also needs satellites with different functions to carry out cooperation, but due to the fixity of the satellite functions, the hybrid constellation is designed for a single function, and only certain differentiation is carried out on the coverage area aiming at the cooperation characteristic. Similarly, the method also aims at the design of a mixed constellation of an electronic remote sensing satellite, an optical imaging satellite and a synthetic aperture radar imaging satellite, and also belongs to a constellation design method of the same observation domain from the perspective of a resource domain.
In another existing research, a low-orbit integrated constellation is designed based on the coverage characteristics of different loads and aiming at the application requirements of communication, navigation and remote sensing integration, and the minimization of constellation data is taken as a target. However, the method directly gives parameters such as satellite height, orbital inclination angle, load constraint and the like, and is equivalent to only give a special case of an integrated constellation. For a cross-domain fusion constellation, parameters and mutual influence relationships of each functional domain need to be considered more comprehensively, which is a design problem of multi-target fusion. In order to more comprehensively carry out optimization design on the cross-domain fusion constellation, a semi-analytical method and an intelligent algorithm such as a genetic algorithm and a multidisciplinary design optimization method are adopted in the prior art. The design of navigation and communication cross-domain fusion shows that the method for optimizing the multidisciplinary design is effective, but for the design of three or more constellations, the algorithm has the problems that the cross-domain fusion constellation cannot directly use an analytical expression, a genetic algorithm is only used in a single discipline or field, and the existing multidisciplinary design optimization method is more the optimization design of different disciplines in a single field, such as structure, orbital dynamics and the like. And no information interaction exists between different disciplines corresponding to different domains, so that the design of a cross-domain fusion constellation is optimized. Therefore, the multidisciplinary optimization method needs to be further improved to adapt to the problems of solving space explosion, variable coupling and information interaction in the cross-domain fusion constellation design.
Disclosure of Invention
Aiming at the defects in the prior art, the invention provides a communication, navigation and remote sensing integrated cross-domain fusion constellation design method based on multidisciplinary cooperation reverse optimization, which divides the constellation design into two stages of comprehensive basic constellation design and basic constellation cross-domain fusion reverse design optimization meeting the requirements, not only can meet the requirements of multi-domain fusion constellation design such as communication, navigation and remote sensing, but also can optimize aiming at an optimization target.
In order to achieve the above object, the present invention provides a method for designing a cross-domain fusion constellation based on multidisciplinary collaborative reverse optimization, comprising the following steps:
step 1, a constellation of each functional domain is independently designed based on task requirements and basic parameters of the constellation to obtain a basic constellation of each functional domain;
and 3, performing reverse optimization on the initial cross-domain fusion constellation, eliminating redundant satellites in the initial cross-domain fusion constellation and deploying optimized satellite loads to obtain the cross-domain fusion constellation.
In one embodiment, the base constellation includes a communication constellation, a navigation constellation, and a remote sensing constellation.
In one embodiment, in the process of synthesizing the basic constellation of each functional domain based on cooperative optimization, the cooperative optimization is divided into general type parameter optimization and special type parameter optimization for optimization;
the design variables of the general parameter optimization are shared by all the functional domains, and the optimization is carried out in the design process of each functional domain;
the design variables of the special parameter optimization are unique to each functional domain, and are optimized only in the design process of the corresponding functional domain.
In one embodiment, the optimization goal of the general parameter optimization is to minimize system cost and expected value of cooperative variables, and the optimization goal of the special parameter optimization is to achieve optimal service performance of each functional domain.
In one embodiment, the optimization objectives of the generic parameter optimization are:
wherein the content of the first and second substances,
a model of a cost calculation of the system is represented,
variables representing participation of each functional domain in system cost calculations,
the expected values of the cooperative variables of the first functional domain participating in the design are shown, and by analogy, 1,2,3,4 in the optimization targets represent four functional domains of communication, navigation, remote sensing and other domains in the example respectively,
indicating that the function domain passes, the variables participating in the optimization of the general parameters,
a variable representing the expected value of a generic parameter. It should be noted that the 4 th domain in the above optimization objective is only illustrative of supporting the expansion of other domains, and the domain is not available in the cross-domain fusion design of the three domains of communication, navigation and remote sensing.nThe number of variables which are transmitted by the functional domain to participate in the optimization of the general parameters is represented, and the value of each functional domain is not necessarily the same.
In one embodiment, the optimization goals for the communication domain's specialized parameter optimization are:
wherein, the first and the second end of the pipe are connected with each other,
representing the minimum coverage of the integrated constellation,
the area of coverage is shown as,
indicating the user minimum elevation angle.
In one embodiment, the optimization goal of the specialized parameter optimization of the navigation domain is:
wherein, the first and the second end of the pipe are connected with each other,
representing the geometric dilution of precision.
In one embodiment, the optimization goals for the specialized parameter optimization of the remote sensing domain are:
wherein, the first and the second end of the pipe are connected with each other,
the area of coverage is shown as,
representing the angle of the field of view of the satellite load,
representing the minimum satellite load field of view angle,
representing the maximum satellite load field angle.
In one embodiment, the criteria for rejecting redundant satellites in the process of performing inverse optimization on the initial cross-domain fusion constellation are as follows:
for a sensor in the initial cross-domain fusion constellation, sequentially placing the sensor on a satellite of a satellite cluster in a satellite cluster visible to a target area, and then calculating the change of the service performance of the satellite cluster after movement;
after all the satellites are moved, sequencing the improvement of the service performance of the cluster by the position change of each satellite, and if the improvement is better than that before the movement and meets the service requirement, taking the optimal position as a new sensor deployment position;
and after the deployment of the sensors in the initial cross-domain fusion constellation is circulated, removing the satellites without the sensors.
In one embodiment, the number of sensors deployed per satellite is limited when deploying the sensors.
The invention has the following beneficial technical effects:
1. the invention provides an innovative concept of an integrated cross-domain fusion constellation, the constellation can provide integrated space-based services such as communication, navigation and remote sensing, and has advantages in services such as satellite quantity, cost and service;
2. the invention provides a two-stage constellation design method for multidisciplinary collaborative design of a basic constellation and reverse design optimization of a fusion type constellation, which can meet the design requirements of multi-domain fusion constellations such as communication, navigation, remote sensing and the like and can optimize aiming at an optimization target;
3. aiming at the basic constellation design, the invention improves the multidisciplinary collaborative design method, and can effectively improve the basic constellation design efficiency by increasing the parameter transmission of each domain in the general parameter and parameter design of each domain, and the method can meet the comprehensive requirements of various services;
4. the invention provides a reverse optimization method based on index constraint aiming at the requirement of cross-domain fusion optimization of a basic constellation, and the method can quickly eliminate redundant satellites under the condition of ensuring that a constellation meets the index requirement, thereby realizing the optimization design of the constellation.
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In order to more clearly illustrate the embodiments or technical solutions of the present invention, the drawings used in the embodiments or technical solutions of the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the structures shown in the drawings without creative efforts.
FIG. 1 is a flow chart of a cross-domain fusion constellation design method according to an embodiment of the present invention;
FIG. 2 is a flow chart of multidisciplinary collaborative reverse engineering in an embodiment of the present invention;
FIG. 3 is a diagram of a multidisciplinary collaborative design structure of a cross-domain fusion constellation in an embodiment of the present invention;
fig. 4 is a diagram illustrating multiple resource coverage of a target area according to an embodiment of the invention.
The implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In addition, the technical solutions in the embodiments of the present invention may be combined with each other, but it must be based on the realization of the technical solutions by those skilled in the art, and when the technical solutions are contradictory to each other or cannot be realized, such a combination of the technical solutions should not be considered to exist, and is not within the protection scope of the present invention.
The embodiment discloses a cross-domain fusion constellation design method based on multidisciplinary cooperation reverse optimization, which divides constellation design into two stages of comprehensive basic constellation design and basic constellation cross-domain fusion reverse design optimization which meet requirements. Traditional constellation design is generally directed to single services, such as designing dedicated navigation constellations, remote sensing constellations. Aiming at the requirement of integrating multiple services of a cross-domain fusion constellation, a traditional constellation design party can be effectively adopted. In the first stage, the present embodiment first performs independent design on the constellation of each domain to obtain the constellation meeting the requirements of each service, and then performs synthesis. And then, in the second stage, reverse design is carried out according to index requirements, cross-domain fusion optimization design is carried out on the constellation, redundant satellites are deleted, and an optimized constellation scheme is obtained.
Referring to fig. 1, the method for designing a cross-domain fusion constellation in this embodiment specifically includes the following steps:
step 1, a constellation of each functional domain is independently designed based on task requirements and basic parameters of the constellation to obtain a basic constellation of each functional domain;
and 3, performing reverse optimization on the initial cross-domain fusion constellation, eliminating redundant satellites in the initial cross-domain fusion constellation and optimizing satellite loads to obtain the cross-domain fusion constellation.
The traditional constellation design is to design a single-domain functional system. The integrated cross-domain fusion constellation is a multi-domain general constellation, and the completed tasks are not limited to a certain class any more. In this embodiment, communication, navigation, and remote sensing are taken as examples for explanation, that is, the basic constellation in step 1 includes a communication constellation, a navigation constellation, and a remote sensing constellation.
In the design process of the basic constellation, the system requirements and constraints of the constellation need to be analyzed first. In order to meet the service requirements of cross-domain fusion, the requirements of each domain need to be combined as much as possible, and then the requirements which cannot be combined are designed independently, so that services of each domain can construct constellations independently, independent operation is supported, and cooperative work can be realized. The cross-domain fusion constellation efficiently plays the advantages of large high-orbit coverage area and high low-orbit detection resolution by cooperating with multi-layer constellations with different heights and different functions. Due to cooperation among satellites, the cross-domain fusion constellation can effectively optimize the number of the orbital layers, the number of the satellites and the arrangement of loads, so that the advantages of the number of the satellites and the construction cost can be brought on the premise of meeting the performance of service requirements. The method has great significance for the construction of low-orbit giant satellite constellations, the reduction of the number of satellites in the orbital space, the reduction of the number of fragments in the space environment and the like.
In a specific implementation process, a design flow of a cross-domain fusion constellation is shown in fig. 2. Basic task requirements are firstly configured, such as whether the coverage target is regional or global; service requirements such as coverage requirements of the remote sensing domain. Since the satellite of the cross-domain fusion constellation can define the satellite function in orbit through software, but is constrained by the load carried by the satellite, the constraint condition of the corresponding load needs to be given. The next step is to set basic parameter constraints of the constellation satellite, such as orbit height, orbit inclination angle, etc. The height aspect can set a certain strategy, such as setting the height range of the high, medium and low tracks and the proportion of each layer. The basic parameters of the constellation cannot determine specific values in the previous period, but can give an approximate limited range; more precise range definition can greatly reduce the amount of computation. And performing multidisciplinary collaborative constellation design based on the task requirements and the input of basic parameters of the constellation satellite to obtain a basic constellation of each functional domain, respectively obtaining a communication constellation, a navigation constellation and a remote sensing constellation, and then performing comprehensive design. In the integration, the satellite is roughly rejected. The mergeable satellites are then merged, i.e., fused, in the reverse design phase. And outputting the final target constellation after reverse optimization based on index constraint. The output mainly comprises basic parameter information of a cross-domain fusion constellation and single satellite load distribution information.
In this embodiment, the method for generating a communication constellation in a basic constellation includes:
in the ultra-dense low-orbit satellite-ground communication, a user is concerned about the communication backhaul capacity, and the service quality obtained by the user is reflected. The main indicator of the communication constellation takes into account the communication backhaul capacity of the user terminal. Hypothetical satellite
Under the coverage area of
Individual user terminal
Then the communication capacity of each user terminal
Comprises the following steps:
wherein, the first and the second end of the pipe are connected with each other,
which is indicative of the available bandwidth of the satellite,
representing the number of users within the coverage area of satellite i,
which is indicative of the transmitted power of the satellite,
representing the additive white gaussian noise of the satellite,
representing interference between satellite users.
For each user terminaluIf there ismThe satellite jointly covers the area, and the service capacity obtained by the user terminal is due to the satellite cooperative serviceCA u Comprises the following steps:
wherein the content of the first and second substances,S u representing a satellite constellation;
for a given number of user terminals, the more satellites that cover the user terminals, the greater the total communication backhaul capacity that can be obtained. In this embodiment, a typical LEO polar orbit constellation is used as an initial constellation, and the polar orbit constellation has a good coverage advantage in communication, so the polar orbit constellation with global multiple coverage is considered in this embodiment. The objective of the communication constellation in this embodiment is to improve the communication backhaul capacity by covering as much satellites as possible while maintaining the minimum elevation angle of the user. Meanwhile, in order to ensure the continuity of communication, the communication constellation needs to ensure that the revisit time of the user is as small as zero as possible.
In this embodiment, the navigation constellation generation method in the basic constellation is as follows:
the low-orbit navigation enhancement is the capability of improving the precision, the integrity and the space-based monitoring of the traditional medium-high orbit satellite navigation system by using a low-orbit constellation. The low-orbit navigation enhancement is divided into the following steps according to the technical system: low-orbit independent navigation and low-orbit navigation enhancement. The low-orbit independent navigation is a low-orbit satellite broadcast type GNSS signal, provides independent navigation service, and can be used as one of backup positioning navigation and time service technical means. The main indicator is the available navigation accuracy factor PDOP. Taking the mixture of the inclined orbit and the polar orbit of the micro-space navigation constellation as an example, suppose the number of the orbit surfaces isNThe number of the track surfaces isPThe phase factor isFThe height of the track ishThe track inclination angle is
. In the independent working mode, only LEO constellation and state vector are considered
The description is as follows:
wherein, the first and the second end of the pipe are connected with each other,
which is indicative of a user-positioned parameter,
the receiver clock delay representing the LEO constellation,cis the speed of light. Weight system matrixHCan be described as follows:
wherein the content of the first and second substances,
representing the number of satellites in view in the LEO constellation,
and
respectively representing an LEO satellite position vector and a user position vector under an Earth-Centered Earth Fixed coordinate system (ECEF). Assuming that measurements from different LEO satellites have the same accuracy, the DOP of H is expressed as follows:
accuracy of DOP-based satellite navigation positioning systems, PDOP in general<And 5, better navigation and positioning performance can be obtained. Suppose the system requirements of PDOP are
Then, the calculation formula of the global GDOP is as follows:
wherein the content of the first and second substances,GDOP globe which represents the GDOP of the world in general,latthe value of the latitude index is represented,lona value representing the index of the longitude is indicated,Epocha value of the time index is represented,Trepresenting the time period involved in the computation of the GDOP,N t indicates the number of divided slots and,N lon indicates the number of the longitude divisions,N lat representing the number of latitude divisions.
In this embodiment, the method for generating the remote sensing constellation in the basic constellation includes:
the remote sensing constellation generally focuses on coverage area and observation resolution. The coverage area is generally related to the target area. The observation resolution determines the quality of service of the remote sensing constellation. Setting a maximum value of a required observation resolution of a remote sensing constellation asrs And m is selected. Assuming satellite orbital altitude ofhThe radius of the earth isR e The angle of the satellite load field is
The ground covering width isL，aIs semi-major axis, then satellite coverageLThe calculation formula is as follows:
Lthe coverage area of a single satellite on the earth is required to realize global single coverage, and the sum of the coverage areas of all satellites of a constellation is generally twice of the total area of the ground. The coverage area of the remote sensing load needs to achieve 2 times the coverage. The earth observation load sensor mainly comprises radar, optical machine scanning and charge coupled device, etc., although their respective principles are different, their spatial resolution ratioE rsl All associated with the instantaneous field of view
(or aperture) and track heighthThe correlation is as follows:
wherein, the first and the second end of the pipe are connected with each other,
in relation to sensor size and scanner focal length (or imaging plate pixel matrix size), the performance quality is related to the component device. As can be seen from the equation, the lower the orbit, the higher the resolution can be obtained. So it also relates to optimization of the number of satellites and the orbital altitude.
After the basic constellation design is completed, the basic constellation with each functional domain individually designed, such as navigation, communication, remote sensing, and the like, is constructed into a comprehensive constellation, i.e., the initial cross-domain fusion constellation in step 2. The integrated cross-domain fusion constellation involves more variables, and the relationship of mutual influence and restriction among all sub-constellations needs to be considered. Such as the number of satellites, the number of orbital planes, and the orbital altitude, all of which affect the service performance of the three types of constellations in the base constellation. For the requirements of integrated cross-domain fusion constellations, in this embodiment, collaborative optimization is divided into general parameter optimization and special parameter optimization for optimization, where the design variables of the general parameter optimization include the number of satellites, the height of the orbit, the inclination angle of the orbit, and the like, and these general design variables are shared by the sub-problems of each functional domain and participate in the design optimization process of the sub-problems of each functional domain. The design variables of the special parameter optimization are unique to each functional domain, and the optimization is only carried out in the design process of each functional domain.
Since the integrated cross-domain fusion constellation spans the fields of communication, navigation, remote sensing and the like, in order to perform unified measurement on each parameter of the system, a unified method based on cost measurement is adopted in the embodiment. And aiming at each domain such as communication, navigation, remote sensing and the like, service performance indexes are unified to a cost scale, and cost-based optimization is performed on special parameters. The structure of the multidisciplinary optimization method of hierarchical collaborative optimization is shown in FIG. 3. The optimization goal for the generic type of parameters is to minimize system cost. The objective of the specific parameters is to achieve the optimal service performance of each functional domain, such as the highest precision in the navigation domain, while satisfying the system constraints.
In synthesis, the cost of the cross-domain fusion constellation mainly considers the number of satellites and the cost of a single satellite. The cost of a single satellite mainly considers the cost of a satellite foundation platform and a load, and it is worth pointing out that the cost of the space-based system also includes the cost of transmission and the cost of operation and maintenance, which is not considered too much in this embodiment:
wherein the content of the first and second substances,C platform andC paylosd respectively the cost of the satellite platform and the load. Assume a platform for a satellite, but the amount of payload is determined based on the optimal deployment. And the number of the satellite is not more than 3 due to the limitation of the volume power consumption of the satellite. The use of standardized satellite platforms and mass producible loads can reduce costs. In this embodiment, the established optimization model is as follows:
the optimization target of the general parameter optimization is as follows:
wherein the content of the first and second substances,
a model of a cost calculation of the system is represented,
variables representing the participation of each functional domain in the system cost calculation,
expected values of the cooperative variables representing the first functional domain to participate in the design, and so on, 1,2,3,4 in equation (12) represent real values, respectivelyFour functional domains in the example communication, navigation, remote sensing and others,
indicating that the function domain passes, the variables participating in the optimization of the general parameters,
a variable representing the expected value of a generic parameter. It should be noted that the 4 th domain in the example only illustrates the domain supporting the expansion of other domains, and the domain is not used in the cross-domain fusion design of the communication domain, the navigation domain and the remote sensing domain.nThe number of variables which are transmitted by the functional domain to participate in the optimization of the general parameters is represented, and the value of each functional domain is not necessarily the same.
The optimization targets of the special parameter optimization of the communication domain are as follows:
wherein, the first and the second end of the pipe are connected with each other,
representing the minimum coverage of the integrated constellation,
the area of coverage is shown as,
represents a user minimum elevation; the above constraints indicate that the minimum coverage of the constellation is greater than or equal to 1, the coverage area exceeds 95%, and the minimum elevation angle of the user cannot be lower than 5 °.
The optimization target of the special parameter optimization of the navigation domain is as follows:
the above constraint indicates that the GDOP value of the constellation is less than 5.
The optimization target of the special parameter optimization of the remote sensing domain is as follows:
the constraint of the above formula represents the field angle constraint of the remote sensing load at
Within the range of (1).
Although the embodiment is only directed to the most common communication and navigationDesign optimization is carried out by remote sensing, but other functional domain designs can also be used if other functional domain designs exist in the specific application process
And
to represent and participate in the design of the constellation. Extensions to other functional domains may be designed for demand. Since the method does not limit the number of subjects involved in the collaborative optimization.
And 2, obtaining a comprehensive initial cross-domain fusion constellation. However, the initial cross-domain fusion constellation is relatively redundant, so that the optimization is performed by a cross-domain fusion reverse design method in this embodiment. Namely, by changing relevant design parameters, a cross-domain fusion constellation design scheme is output again, so that on the premise of ensuring service performance, the purpose of comparing a plurality of sets of cross-domain fusion constellation design schemes with the objective of lowest constellation cost and maximum value is realized, and the optimal cross-domain fusion constellation is obtained.
The low-orbit giant constellation has a high spatial orbit density, so there is a description of a super-dense constellation. The advantage is that the satellite earth coverage weight is increased. The following definitions are given here in this example:
an areaAPoint of (5)a，
If attAt least the time iskAn individual has a certain class of load resourcesrjIs called astTime of dayaIs characterized in thatkHeavy loadjAnd (6) covering the resources. If regionAAll points in (1) arekOverlap, then called areaAIs thatkHeavy loadjAnd (4) covering the resources.
For low-orbit ultra-dense constellations, low-orbit satellites generally consume less power in volume. Due to the limitation of volume power consumption, the cross-domain fused satellite generally cannot carry a great amount of various loads, which not only puts high requirements on the satellite integration technology, but also makes part of the loads difficult to be compatible. More importantly, due to multiple resource coverageIn fact, resources are wasted, and the cost of building the cross-domain fusion constellation as an infrastructure is greatly increased. Therefore, load deployment can be optimized according to requirements, for example, in the case shown in fig. 4, the coverage area is only required to be covered by 2, and therefore, the satellite 2, the satellite 4 and the load can be deleted optimally. For communicating and remotely sensing loads, the load is first consideredkAnd (4) the coverage degree is repeated. Here, we give directlykThe sufficient conditions of the repeated coverage degree are as follows:
introduction 1: quilt on earth surfacej(Resource)kAnd (4) re-covering when the following conditions are met: 1 is if two satellites have an intersection; 2 is that all intersections are at leastkAnd (4) re-covering. And the coordinates of the intersection point are:
the paper "X, wang, G, xing, Y, zhang, C, lu, R, pless, and C, gill," Integrated coverage and connectivity configuration in Wireless Sensor networks, "in Proc. 1st Int. Conf. Embedded Net. Sensor Syst, 2003, pp. 28-39" gives a binary equation for λ, which in this example further gives the expression for λ:
wherein (x) 1 、y 1 、z 1 ）、（x 2 、y 2 、z 2 ) Respectively representing the coordinates of the two intersection points in the geocentric rectangular coordinate system.
For GDOP, assuming a minimum of four satellites carrying navigation loads are required, the GDOP system hasnIn a cluster of satellites, the number of possible combinations is:
in the case of sequentially varying positions of the navigation load, a total calculation is required
Next, the process is repeated. And then taking the position with the minimum GDOP value as the position of the navigation load after optimization.
In this embodiment, the standard for rejecting redundant satellites in the process of performing reverse optimization on the initial cross-domain fusion constellation is as follows:
for a sensor in the initial cross-domain fusion constellation, sequentially placing the sensor on a satellite of a satellite cluster in a satellite cluster visible to a target area, and then calculating the change of the service performance of the satellite cluster after movement;
after all the satellites are moved, sequencing the improvement of the service performance of the cluster by the position change of each satellite, and if the improvement is better than that before the movement and meets the service requirement, taking the optimal position as a new sensor deployment position;
and after the deployment of the sensors in the initial cross-domain fusion constellation is circulated, removing the satellites without the sensors.
As a preferred embodiment, the number of sensors deployed per satellite may be limited when deploying the sensors.
In the elimination process, the elimination standard of the navigation load is shown in the foregoing, and if the GDOP value of the navigation resource in the cluster is smaller than the original deployment position under the new deployment position, the load adopts the new deployment position. It should be noted that, in the present embodiment, a limit is set to the number of loads deployed per satellite. This is also a consideration of the volumetric power consumption limitations in practical satellites.
The above description is only a preferred embodiment of the present invention, and is not intended to limit the scope of the present invention, and all modifications and equivalents of the present invention, which are made by the contents of the present specification and the accompanying drawings, or directly/indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (8)
1. A cross-domain fusion constellation design method based on multidisciplinary collaborative reverse optimization is characterized by comprising the following steps:
step 1, independently designing the constellation of each functional domain based on task requirements and basic parameters of the constellation to obtain a basic constellation of each functional domain;
step 2, synthesizing the basic constellation of each functional domain based on cooperative optimization to obtain an initial cross-domain fusion constellation;
and 3, performing reverse optimization on the initial cross-domain fusion constellation, eliminating redundant satellites in the initial cross-domain fusion constellation and deploying optimized satellite loads to obtain the cross-domain fusion constellation.
2. The multidisciplinary collaborative reverse optimization-based cross-domain fusion constellation design method according to claim 1, wherein the cross-domain fusion constellation includes but is not limited to a communication constellation, a navigation constellation and a remote sensing constellation;
the cross-domain fusion constellation is a space-based infrastructure formed by cross-domain fusion of constellations of different functional domains, which has the capability of mutual cooperative work and can provide space-based calculation, storage and communication, navigation and remote sensing integrated services, and the constellation types are not limited, but the constellation types have model parameters which can be unified into all the functional domains.
3. The method for designing a cross-domain fusion constellation based on multidisciplinary collaborative reverse optimization according to claim 2, wherein in the process of synthesizing the basic constellation of each functional domain based on collaborative optimization, collaborative optimization is divided into general type parameter optimization and special type parameter optimization for optimization;
the design variables of the general parameter optimization are shared by all the functional domains, and the optimization is carried out in the design process of each functional domain;
the design variables of the special parameter optimization are unique to each functional domain, and are optimized only in the design process of the corresponding functional domain.
4. The method according to claim 3, wherein the optimization objective of the general-purpose parametric optimization is multi-objective optimization including minimizing system cost, and the optimization objective of the special-purpose parametric optimization is to achieve optimal service performance of each functional domain.
5. The method of claim 4, wherein the optimization goal of the generic parameter optimization is to minimize system cost, and the system cost is derived from each functional domain participating in constellation design; and each functional domain unifies the cost model of the domain where the functional domain is located to a general parameter optimization target, participates in the optimization process of the overall design, and is embodied in a minimized mode through a collaborative variable expectation value.
6. The method for designing a cross-domain fusion constellation based on multidisciplinary collaborative reverse optimization according to claim 5, wherein the dedicated parameters of the functional domains participating in the collaborative design optimization are the same or different and are related to the task requirement or performance requirement of the functional domain;
the optimization target of the special parameter optimization of the communication domain is to meet the minimum coverage of communication resources and the minimum user elevation under the constraint of coverage area ratio;
the optimization target of the special parameter optimization of the navigation domain is that the geometric precision factor is minimum under the condition of meeting the coverage of navigation resources;
the optimization target of the special parameter optimization of the remote sensing domain is the fastest revisit time under the constraints of the load field angle and the coverage of the remote sensing resource.
7. The method for designing a cross-domain fusion constellation based on multidisciplinary collaborative reverse optimization according to any one of claims 1 to 6, wherein the criteria for removing redundant satellites in the process of performing reverse optimization on the initial cross-domain fusion constellation are as follows:
for a sensor in an initial cross-domain fusion constellation, sequentially placing the sensor on a satellite of a satellite cluster in the satellite cluster visible to a target area, and calculating the change of the service performance of the satellite cluster after movement;
after all the satellites are moved, sequencing the improvement of the service performance of the cluster by the position change of each satellite, and if the improvement is better than that before the movement and meets the service requirement, taking the optimal position as a new sensor deployment position;
and after the deployment of the sensors in the initial cross-domain fusion constellation is circulated, removing the satellites without the sensors.
8. The method of claim 7, wherein the number of deployed sensors per satellite is limited to match the constraints of satellite size and power consumption when deploying sensors.
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